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ejbs

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CUDA Grep 7 years ago

They did not include the time it took to transfer the input file from memory to the GPU

To give some context: PCIe 3.0 x16 achieves about 11-12 GB/s. So, transfers for benchmarked 53MB file would add ~4.8 ms (per direction, assuming pinned host memory)

Now, they could also pursue a streaming approach, processing in "micro-batches". I.e., pipelining input transfers (HOST->GPU), GPU-based processing, and transfer of results (GPU->HOST), as pursued by [1] (disclaimer: I'm a co-author). This lower's processing latency. Since the interconnect is full-duplex, it would just limit the processing rate to about ~11 GB/s (i.e., 5 ms for mentioned 53MB). To be fair, though, input has to be sufficiently large, such that there are (a) enough micro-batches to overlap transfer and compute and (b) the micro-batches can be chosen to be still large enough to exploit full parallelism of the GPU.

[1] https://arxiv.org/pdf/1905.13415.pdf

Interesting that they're shifting towards AMD GPUs. Was actually hoping for a major update of the MBPR with the availability of NVIDIA's new maxwell architecture and broadwell based quad cores.

Anyone knows why AMD? Is it a margin/profitibility or performance thing?